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This guide is intended for anyone having zero or a small background in programming, maths, and machine learning. There is no specific order to follow, but a classic path would be from top to bottom. If you don't like reading books, skip it, if you don't want to follow an online course, you can skip it as well. There is not a single way to become a machine learning expert and with motivation, you can absolutely achieve it.
All resources listed here are free, except some online courses and books, which are certainly recommended for a better understanding, but it is definitely possible to become an expert without them, with a little more time spent on online readings, videos and practice. When it comes to paying courses, the links in this guide are affiliated links. Please, use them if you feel like following a course as it will support me. Thank you, and have fun learning! Remember, this is completely up to you and not necessary. I felt like it was useful to me and maybe useful to others as well.
Don't be afraid to repeat videos or learn from multiple sources. Repetition is the key of success to learning!
Maintainer - louisfb01
Feel free to message me any great resources to add to this repository on bouchard.lf@gmail.com
Tag me on Twitter @Whats_AI or LinkedIn @Louis (What's AI) Bouchard if you share the list!
This is the best way to start from nothing in my opinion. Here, I list a few of the best videos I found that will give you a great first introduction of the terms you need to know to get started in the field.
Introduction to the most used terms
Understand the neural networks
Here is a list of awesome courses available on YouTube that you should definitely follow and are 100% free.
Introduction to machine learning - YouTube Playlist (Stanford)
Introduction to deep learning - YouTube Playlist (MIT)
Deep learning specialization - YouTube Playlist (Deeplearning.ai)
Deep Learning (with PyTorch) - NYU, Yann LeCun
MIT Deep Learning - Lex Fridman's up-to-date deep learning course
Here is a list of awesome articles available online that you should definitely read and are 100% free. Medium is pretty much the best place to find great explanations, either on Towards AI or Towards Data Science publications. I also share my own articles there and I love using the platform. You can subscribe to Medium using my affiliated link here if this sounds interesting to you and if you'd like to support me at the same time!
Here are some great books to read for the people preferring the reading path.
Great books for building your math background:
A complete Calculus background:
These books are completely optional, but they will provide you a better understanding of the theory and even teach you some stuff about coding your neural networks!
Don't stress, just like most of the things in life, you can learn maths! Here are some great beginner and advanced resources to get into machine learning maths. I would suggest starting with these three very important concepts in machine learning (here are 3 awesome free courses available on Khan Academy):
Here are some great free books and videos that might help you learn in a more "structured approach":
If you still lack mathematical confidence, check out the Read books section above, where I shared many great books to build a strong mathematical background. You now have a very good math background for machine learning and you are ready to dive in deeper!
Here is a list of some great courses to learn the programming side of machine learning.
If you prefer to be more guided and have clear steps to follow, these courses are the best ones to do.
The most important thing in programming is practice. And this applies to machine learning too. It can be hard to find a personal project to practice.
Fortunately, Kaggle exists. This website is full of free courses, tutorials and competitions. You can join competitions for free and just download their data, read about their problem and start coding and testing right away! You can even earn money from winning competitions and it is a great thing to have on your resume. This may be the best way to get experience while learning a lot and even earn money!
You can also create teams for kaggle competition and learn with people! I suggest you join a community to find a team and learn with others, it is always better than alone. Check out the next section for that.
A Discord server with many AI enthusiasts - Learn together, ask questions, find kaggle teammates, share your projects, and more.
A Discord server where you can stay up-to-date with the latest AI news - Stay up-to-date with the latest AI news, ask questions, share your projects, and much more.
Follow reddit communities - Ask questions, share your projects, follow news, and more.
Subscribe to YouTube channels that share new papers - Stay up to date with the news in the field!
LinkedIn Groups
Facebook Groups
Newsletters
Follow Medium accounts and publications
Check this complete GitHub guide to keep up with AI News
Tag me on Twitter @Whats_AI or LinkedIn @Louis (What's AI) Bouchard if you share the list!
If you'd like to support me, I have a Patreon where you can do that. Thank you, and let me know if I missed any good resources!
This guide is still regularly updated.
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